learn

Perform web searches and store actionable takeaways in MemoryGraph.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/ste-bah/archon --skill learn-ste-bah
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: learn
Source: https://github.com/ste-bah/archon/tree/main/.claude/skills/learn
Command: npx skills add https://github.com/ste-bah/archon --skill learn-ste-bah

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates self-directed topic research, captures actionable takeaways, and stores them in MemoryGraph to reduce knowledge debt and support continuous learning.

Core Features & Use Cases

  • Auto-select topics based on knowledge gaps and active projects to prioritize learning.
  • Perform web searches, extract takeaways, and persist them with source URLs for citation.
  • Loop into ongoing memory improvements, enabling autonomous background learning and incremental memory growth.

Quick Start

Provide a topic to learn, or let memory gaps drive auto-topic selection.

Frequently Asked Questions about learn

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate self-directed topic research to fill knowledge gaps?

Automated self-directed topic research works by performing web searches based on explicit topics or detected knowledge gaps, then extracting actionable takeaways and storing them in MemoryGraph to reduce knowledge debt.

Can I auto-select research topics based on my active projects?

Yes, topic auto-selection is supported by relying on knowledge-gap signals from active projects to prioritize and drive autonomous learning without requiring explicit topic input for every query.

How does autonomous learning store web search takeaways for later use?

Autonomous learning captures takeaways from web searches and persists them in MemoryGraph alongside tagged metadata and source URLs, ensuring findings remain cited and accessible for continuous memory growth.

What is the best way to manage a learning budget for background topic research?

Managing a learning budget involves setting constraints on autonomous background research, allowing the system to loop into ongoing memory improvements and perform incremental topic exploration without manual intervention.

Does this approach to knowledge-gap remediation require explicit topic input to start?

No, knowledge-gap remediation does not strictly require explicit topic input; the system can rely on knowledge-gap signals to trigger exploration and automatically select relevant topics to research.